Incident Library
Applied filters Root causeCapacity exhaustionComponentClient-side DNS resolver and cacheDomainKubernetesClear allEvery case under the filters, with no sentence; newest first.
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  • Contributing factor
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Cases7 cases

1 to 5 of 7

  1. Symptoms

    CI jobs failed now and then because a hostname could not be resolved. The failures came from tensorstore, appeared on several different instances and did not repeat consistently. The error read: "./tensorstore/util/result.h:420: Status not ok: status(): UNAVAILABLE: CURL error Could not resolve hostname: Could not resolve host: company-bucket.s3.amazonaws.com".

    Trigger

    An administrative pod running with host networking called sudo in a loop. Each sudo call looked up the node's own hostname, and with ndots:5 and four search domains every lookup became five queries, for both A and AAAA records.

    Root cause
    Component
    Contributing factor
    Detection

    Reports of flaky CI jobs that could not resolve an S3 bucket hostname, followed by i/o timeout errors in the CoreDNS logs.

    Remediation
    • added 'Defaults !fqdn' in /etc/sudoers.d/00-no-fqdn (mode 440) to the container image so sudo stopped looking up the hostname
    Lessons

    Traffic from CoreDNS to the VPC DNS resolver is limited to 1024 packets per second per interface, and drops show up only as UDP timeouts; the linklocal_allowance_exceeded counter in ethtool shows them. Names that are not fully qualified are multiplied by the search domains under ndots:5, and AAAA lookups double them again. sudo looks up the host's own name on every call unless 'Defaults !fqdn' is set.

  2. Symptoms

    Services on the production Amazon EKS cluster behind the idus marketplace threw intermittent errors whose cause was hard to pin down. Calls to external services such as RDS and Redis failed now and then, and whenever DNS traffic spiked, domain lookups answered slowly or failed outright.

    Trigger

    All CoreDNS pods were scheduled onto the same node, and that node's memory usage spiked until it ran out of memory.

    Root cause
    Component
    Contributing factor
    Detection

    The write-up does not say how the full outage was noticed. The earlier DNS trouble showed up as intermittent service errors, and investigating failed calls to RDS and Redis led to DNS resolution failures.

    Remediation
    • deployed NodeLocal DNSCache as a DaemonSet in front of CoreDNS
    • added a PodDisruptionBudget (maxUnavailable 1) and topologySpreadConstraints across zones for CoreDNS
    • lowered ndots from 5 to 2 with dnsConfig in the Deployments
    Lessons

    The CoreDNS setup that EKS creates by default (two pods) can be enough for a small or development cluster but becomes a bottleneck in a large production cluster, and DNS is a single point of failure that needs high availability and room to scale. Tuning the CoreDNS cache and buffer size only relieved the symptoms; the real load came from the extra queries that ndots:5 generates for external names. A CoreDNS pod without a memory limit can share a node's fate with everything else on it.

  3. Symptoms

    A team using Neco, the Kubernetes platform run by Cybozu's Cloud Platform team, reported what looked like a performance problem in the cluster DNS servers. An application in a pod that resolved cluster Services at hundreds of requests per second frequently got `no such host` and `i/o timeout` errors.

    Trigger

    The number of MySQL clusters watched by the monitoring application increased, and after that the name resolution errors became frequent.

    Root cause
    Component
    Contributing factor
    Detection

    A team using the platform contacted the Cloud Platform team, describing the errors as a performance problem in the cluster DNS server.

    Remediation
    • Raised the kernel parameter netdev_max_backlog on the nodes
    • Set up alerts on softnet
    • Wrote a runbook for the softnet alerts
    Action items
    • Evaluate Cilium's netkit device so pod packets bypass the backlog queue
    Lessons

    Raising netdev_max_backlog makes the same failure less likely and the new alerts catch it early, but it is not a root fix: a pod that sends more packets can fill the backlog queue again. Cybozu sees replacing the veth interface with netkit, which skips the backlog queue, as the root fix.

  4. Symptoms

    When MonotaRO raised the share of requests for the remaining endpoints of its backend API sent to EKS from 1% to 25%, Sentry filled with errors saying the API could not reach the database and outside services. The errors were about DNS name resolution, and the traffic had to be shifted back to the EC2 version.

    Trigger

    MonotaRO raised the share of requests for the remaining API endpoints routed by the ALB to the EKS version from 1% to 25%.

    Root cause
    Component
    Contributing factor
    Detection

    Sentry showed a large number of errors about connecting to the database and outside services right after the traffic share was raised.

    Remediation
    • Shifted the requests back to the EC2 version to stop the errors
    • Added an HPA to autoscale the CoreDNS pods as a stopgap, which let the migration to EKS finish
    Action items
    • Set ndots to 1 through dnsConfig in the application Deployments
    • Set cache 600 in the Corefile in the coredns ConfigMap to lengthen the CoreDNS cache TTL
    • Add lameduck 30s to the CoreDNS health plugin so CoreDNS keeps serving while it is scaled in
    • Consider reducing the differences between production and staging, weighed against cost
    Lessons

    MonotaRO assumed that a managed service would not cause problems and so skipped researching other companies' migrations, load testing and monitoring. Staging differed from production in its network layout, so ndots differed between them, and staging databases could not take a high-load test. Looking at the CoreDNS logs and resolv.conf instead of guessing found that ndots:5 made lookups of outside names try every search domain first.

  5. Symptoms

    In 2020 Chatwork moved its legacy system from EC2 to EKS, running both sides in parallel with Route53 weighted records. Once more than a certain share of requests was sent to the EKS side, the service suddenly became unstable. On some nodes the conntrack table had gone past its limit and connections to the application were being dropped.

    Trigger

    During the migration from EC2 to EKS, Chatwork sent more than a certain share of requests to the EKS side. Later, applying node-local-dns with force_tcp in its configuration made DNS unstable again.

    Root cause
    Component
    Contributing factor
    Remediation
    • Raised the conntrack maxPerCore value in the kube-proxy configuration
    • Installed dns-autoscaler so CoreDNS ran with more pods
    • Installed node-local-dns as a DaemonSet on every node
    • Replaced force_tcp with prefer_udp in the node-local-dns configuration
    Lessons

    On EKS, dns-autoscaler and node-local-dns made DNS stable, but node-local-dns must not use force_tcp there. Stable DNS also matters for sizing the number of pods correctly, since blocked DNS queries had made the pod count grow.

Check your cluster for this

These 7 cases involve Client-side DNS resolver and cache and CoreDNS. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

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